Overview

Dataset statistics

Number of variables59
Number of observations50000
Missing cells1418222
Missing cells (%)48.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.5 MiB
Average record size in memory472.0 B

Variable types

CAT47
NUM9
BOOL3

Warnings

Visibility has constant value "50000" Constant
EVENTDATA_BINARY has a high cardinality: 227 distinct values High cardinality
EVENTDATA_DATA has a high cardinality: 2398 distinct values High cardinality
EVENTDATA_DATA_PARAM1 has a high cardinality: 63 distinct values High cardinality
EVENTDATA_DATA_SCHANNELNAME has a high cardinality: 27717 distinct values High cardinality
EVENTDATA_DATA_USERNAME has a high cardinality: 5386 distinct values High cardinality
EVENTDATA_DATA_WORKSTATIONNAME has a high cardinality: 4002 distinct values High cardinality
FILENAME_INGEST has a high cardinality: 14146 distinct values High cardinality
LOCATION has a high cardinality: 77 distinct values High cardinality
SITE_COLLECTION has a high cardinality: 282 distinct values High cardinality
SYSTEM_COMPUTER has a high cardinality: 282 distinct values High cardinality
SYSTEM_COMPUTER_REVERSE has a high cardinality: 282 distinct values High cardinality
SYSTEM_TIMECREATED_SYSTEMTIME has a high cardinality: 49939 distinct values High cardinality
SYSTEM_EVENTID is highly correlated with EVENTDATA_DATA_SCHANNELTYPE and 1 other fieldsHigh correlation
EVENTDATA_DATA_SCHANNELTYPE is highly correlated with SYSTEM_EVENTIDHigh correlation
SYSTEM_EVENTRECORDID is highly correlated with EVENTDATA_DATA_REQUESTIDHigh correlation
EVENTDATA_DATA_REQUESTID is highly correlated with SYSTEM_EVENTRECORDIDHigh correlation
USERDATA_EVENTXML_BINARYDATASIZE is highly correlated with SYSTEM_EVENTIDHigh correlation
ARCHITECTURE has 16962 (33.9%) missing values Missing
DOMAIN has 16962 (33.9%) missing values Missing
DOMAINCONTROLLER has 16962 (33.9%) missing values Missing
DOMAINCONTROLLERNUMBER has 16962 (33.9%) missing values Missing
EVENTDATA_BINARY has 49655 (99.3%) missing values Missing
EVENTDATA_DATA has 47146 (94.3%) missing values Missing
EVENTDATA_DATA_ADDITIONALERRORMESSAGE has 49999 (> 99.9%) missing values Missing
EVENTDATA_DATA_ADDITIONALINFORMATION has 49994 (> 99.9%) missing values Missing
EVENTDATA_DATA_DN has 49999 (> 99.9%) missing values Missing
EVENTDATA_DATA_DOMAINNAME has 11367 (22.7%) missing values Missing
EVENTDATA_DATA_ERRORMESSAGETEXT has 49999 (> 99.9%) missing values Missing
EVENTDATA_DATA_HOSTNAME has 49999 (> 99.9%) missing values Missing
EVENTDATA_DATA_PARAM1 has 49746 (99.5%) missing values Missing
EVENTDATA_DATA_PARAM2 has 49972 (99.9%) missing values Missing
EVENTDATA_DATA_PARAM3 has 49985 (> 99.9%) missing values Missing
EVENTDATA_DATA_REASON has 49994 (> 99.9%) missing values Missing
EVENTDATA_DATA_REQUESTID has 49993 (> 99.9%) missing values Missing
EVENTDATA_DATA_SCHANNELNAME has 3243 (6.5%) missing values Missing
EVENTDATA_DATA_SCHANNELTYPE has 3243 (6.5%) missing values Missing
EVENTDATA_DATA_SUBJECTNAME has 49994 (> 99.9%) missing values Missing
EVENTDATA_DATA_USERNAME has 3243 (6.5%) missing values Missing
EVENTDATA_DATA_WORKSTATIONNAME has 5253 (10.5%) missing values Missing
EVENTDATA_NAME has 49740 (99.5%) missing values Missing
LOCATION has 16962 (33.9%) missing values Missing
SYSTEM_EVENTID_QUALIFIERS has 47031 (94.1%) missing values Missing
SYSTEM_EXECUTION_PROCESSID has 2372 (4.7%) missing values Missing
SYSTEM_EXECUTION_THREADID has 2372 (4.7%) missing values Missing
SYSTEM_OPCODE has 2372 (4.7%) missing values Missing
SYSTEM_PROVIDER_EVENTSOURCENAME has 49403 (98.8%) missing values Missing
SYSTEM_PROVIDER_GUID has 2372 (4.7%) missing values Missing
SYSTEM_SECURITY_USERID has 2629 (5.3%) missing values Missing
SYSTEM_VERSION has 2372 (4.7%) missing values Missing
USERDATA_EVENTXML_BINARYDATA has 49981 (> 99.9%) missing values Missing
USERDATA_EVENTXML_BINARYDATASIZE has 49981 (> 99.9%) missing values Missing
USERDATA_EVENTXML_PARAM1 has 49981 (> 99.9%) missing values Missing
USERDATA_EVENTXML_PARAM2 has 49990 (> 99.9%) missing values Missing
USERDATA_RMRESTARTEVENT_APPLICATIONS_APPLICATION has 49999 (> 99.9%) missing values Missing
USERDATA_RMRESTARTEVENT_NAPPLICATIONS has 49999 (> 99.9%) missing values Missing
USERDATA_RMRESTARTEVENT_REBOOTREASONS has 49999 (> 99.9%) missing values Missing
USERDATA_RMRESTARTEVENT_RMSESSIONID has 49999 (> 99.9%) missing values Missing
USERDATA_RMSESSIONEVENT_RMSESSIONID has 49998 (> 99.9%) missing values Missing
USERDATA_RMSESSIONEVENT_UTCSTARTTIME has 49998 (> 99.9%) missing values Missing
SYSTEM_EXECUTION_PROCESSID is highly skewed (γ1 = 29.09915413) Skewed
SYSTEM_TASK is highly skewed (γ1 = 36.62829847) Skewed
EVENTDATA_DATA_PARAM3 is uniformly distributed Uniform
SYSTEM_TIMECREATED_SYSTEMTIME is uniformly distributed Uniform
USERDATA_RMSESSIONEVENT_UTCSTARTTIME is uniformly distributed Uniform
Id has unique values Unique
SYSTEM_TASK has 2834 (5.7%) zeros Zeros

Reproduction

Analysis started2020-09-27 00:32:57.508581
Analysis finished2020-09-27 00:33:36.150967
Duration38.64 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Id
Categorical

UNIQUE

Distinct50000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
0980b0bfe564c4ff9b51ea6adf170aee
 
1
00538d7bdde8fd771a9ec8f38b94443c
 
1
0175ba9bfdc399d6f08d7fdbf038c3bc
 
1
019eb19342b95c0e36e38b73d1afd58d
 
1
01189c87b2689f8fb0d9f34fed603945
 
1
Other values (49995)
49995 
ValueCountFrequency (%) 
0980b0bfe564c4ff9b51ea6adf170aee1< 0.1%
 
00538d7bdde8fd771a9ec8f38b94443c1< 0.1%
 
0175ba9bfdc399d6f08d7fdbf038c3bc1< 0.1%
 
019eb19342b95c0e36e38b73d1afd58d1< 0.1%
 
01189c87b2689f8fb0d9f34fed6039451< 0.1%
 
03983bebca39af2fdd73f2e66de63d841< 0.1%
 
02b009fb15ee500a96bc361199e73e521< 0.1%
 
038f5d56b0954ecc718d92ff2536835e1< 0.1%
 
00458f07be88862368b2b80f6fd2787f1< 0.1%
 
29702bb27aefb36e61ff36ce34d1679c1< 0.1%
 
Other values (49990)49990> 99.9%
 
2020-09-26T20:33:36.403294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique50000 ?
Unique (%)100.0%
2020-09-26T20:33:36.585806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length32
Mean length32
Min length32

Timestamp
Real number (ℝ≥0)

Distinct49939
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.599831309e+12
Minimum1.5996096e+12
Maximum1.600037885e+12
Zeros0
Zeros (%)0.0%
Memory size390.6 KiB
2020-09-26T20:33:36.760338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1.5996096e+12
5-th percentile1.5996261e+12
Q11.599677307e+12
median1.599834734e+12
Q31.599975568e+12
95-th percentile1.60002258e+12
Maximum1.600037885e+12
Range428284487
Interquartile range (IQR)298260585

Descriptive statistics

Standard deviation140614566.6
Coefficient of variation (CV)8.789337085e-05
Kurtosis-1.426179199
Mean1.599831309e+12
Median Absolute Deviation (MAD)148484458.5
Skewness-0.09087308757
Sum7.999156547e+16
Variance1.977245633e+16
MonotocityNot monotonic
2020-09-26T20:33:36.922934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.599800649e+123< 0.1%
 
1.59967131e+122< 0.1%
 
1.599847819e+122< 0.1%
 
1.599855924e+122< 0.1%
 
1.599619522e+122< 0.1%
 
1.599613239e+122< 0.1%
 
1.599792752e+122< 0.1%
 
1.599854444e+122< 0.1%
 
1.599811205e+122< 0.1%
 
1.599834767e+122< 0.1%
 
Other values (49929)49979> 99.9%
 
ValueCountFrequency (%) 
1.5996096e+121< 0.1%
 
1.599609601e+121< 0.1%
 
1.599609603e+121< 0.1%
 
1.599609606e+121< 0.1%
 
1.599609607e+121< 0.1%
 
ValueCountFrequency (%) 
1.600037885e+121< 0.1%
 
1.60003777e+121< 0.1%
 
1.600037754e+121< 0.1%
 
1.600037702e+121< 0.1%
 
1.600037673e+121< 0.1%
 

Data Type
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
evtx-ntlm-c
46757 
evtx-application-c
 
2678
evtx-dns_server-c
 
253
evtx-directory_service-c
 
204
evtx-dfs_replication-c
 
108
ValueCountFrequency (%) 
evtx-ntlm-c4675793.5%
 
evtx-application-c26785.4%
 
evtx-dns_server-c2530.5%
 
evtx-directory_service-c2040.4%
 
evtx-dfs_replication-c1080.2%
 
2020-09-26T20:33:37.082507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:37.190188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:37.351272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length11
Mean length11.48208
Min length11

Visibility
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
U&FOUO
50000 
ValueCountFrequency (%) 
U&FOUO50000100.0%
 
2020-09-26T20:33:37.487936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:37.575669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:37.662439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

ARCHITECTURE
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing16962
Missing (%)33.9%
Memory size390.6 KiB
P
31932 
p
 
1106
ValueCountFrequency (%) 
P3193263.9%
 
p11062.2%
 
(Missing)1696233.9%
 
2020-09-26T20:33:37.808119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:37.899875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:38.011576image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.67848
Min length1

DOMAIN
Categorical

MISSING

Distinct11
Distinct (%)< 0.1%
Missing16962
Missing (%)33.9%
Memory size390.6 KiB
NE
10883 
SW
8324 
SE
7040 
NW
5282 
se
 
999
Other values (6)
 
510
ValueCountFrequency (%) 
NE1088321.8%
 
SW832416.6%
 
SE704014.1%
 
NW528210.6%
 
se9992.0%
 
HQ3370.7%
 
nw1030.2%
 
DS560.1%
 
CO7< 0.1%
 
ds4< 0.1%
 
(Missing)1696233.9%
 
2020-09-26T20:33:38.172117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:38.310744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.33924
Min length2

DOMAINCONTROLLER
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing16962
Missing (%)33.9%
Memory size390.6 KiB
A1
31932 
a1
 
1106
ValueCountFrequency (%) 
A13193263.9%
 
a111062.2%
 
(Missing)1696233.9%
 
2020-09-26T20:33:38.451369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:38.540162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:38.644849image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length2
Mean length2.33924
Min length2

DOMAINCONTROLLERNUMBER
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing16962
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean1.904867123
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size390.6 KiB
2020-09-26T20:33:38.770516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8393707828
Coefficient of variation (CV)0.44064532
Kurtosis1.379832323
Mean1.904867123
Median Absolute Deviation (MAD)0
Skewness1.097070662
Sum62933
Variance0.704543311
MonotocityNot monotonic
2020-09-26T20:33:38.888230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
21768435.4%
 
11056621.1%
 
423954.8%
 
322844.6%
 
5910.2%
 
615< 0.1%
 
72< 0.1%
 
81< 0.1%
 
(Missing)1696233.9%
 
ValueCountFrequency (%) 
11056621.1%
 
21768435.4%
 
322844.6%
 
423954.8%
 
5910.2%
 
ValueCountFrequency (%) 
81< 0.1%
 
72< 0.1%
 
615< 0.1%
 
5910.2%
 
423954.8%
 

EVENTDATA_BINARY
Categorical

HIGH CARDINALITY
MISSING

Distinct227
Distinct (%)65.8%
Missing49655
Missing (%)99.3%
Memory size390.6 KiB
154800000A000000100000004800550041004300410030004400530056003000530051004C00300031000000070000006D00610073007400650072000000
95 
2A230000
 
13
22000000
 
7
660400C00800000014000000
 
5
7B46343243463138392D304443392D344643322D383030412D4243304637303834383031387D3030303032326430343831353432323734386161623133383132343637626266393331373030303030303030
 
2
Other values (222)
223 
ValueCountFrequency (%) 
154800000A000000100000004800550041004300410030004400530056003000530051004C00300031000000070000006D00610073007400650072000000950.2%
 
2A23000013< 0.1%
 
220000007< 0.1%
 
660400C008000000140000005< 0.1%
 
7B46343243463138392D304443392D344643322D383030412D4243304637303834383031387D30303030323264303438313534323237343861616231333831323436376262663933313730303030303030302< 0.1%
 
7B45323745373446302D304541442D344335442D384636462D3143393139324432344141357D30303030656665306530373636303937633238323033653035306366376137633339646230303030303930342< 0.1%
 
6D3528000100000001000000046E6173650264730461726D79036D696C00000600010F43414D5057305534344244533032360000000100FF0000000000001< 0.1%
 
A03B28000100000001000000046E6173650264730461726D79036D696C00000600010F43414D50505257464A3746463030310000000100FF0000000000001< 0.1%
 
3E0C28000100000001000000046E6173650264730461726D79036D696C00000600010F43414D5057483130414144533031350000000100FF0000000000001< 0.1%
 
F31028000100000001000000046E6173650264730461726D79036D696C00000600010E45543030323142374437333338330000000100FF0000000000001< 0.1%
 
Other values (217)2170.4%
 
(Missing)4965599.3%
 
2020-09-26T20:33:39.062733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique221 ?
Unique (%)64.1%
2020-09-26T20:33:39.218316image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length336
Median length3
Mean length3.78582
Min length3

EVENTDATA_DATA
Categorical

HIGH CARDINALITY
MISSING

Distinct2398
Distinct (%)84.0%
Missing47146
Missing (%)94.3%
Memory size390.6 KiB
ERROR: openkey_set_protection Unable to autoload cardset in silent mode
 
178
caller=svchost.exe
 
48
6.3.9600.19101
 
46
C:\Windows\system32\sppwinob.dll, msft:spp/windowsfunctionality/agent/7.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/inherited/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/phone/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/pkey/detect, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/ActionScheduler/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/TaskScheduler/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/statecollector/pkey, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/volume/services/kms/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/volume/services/kms/activationinfo/1.0, 0x00000000, 0x00000000
 
36
C:\windows\system32\sppwinob.dll, msft:spp/windowsfunctionality/agent/7.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/inherited/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/phone/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/pkey/detect, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/ActionScheduler/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/TaskScheduler/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/statecollector/pkey, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/volume/services/kms/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/volume/services/kms/activationinfo/1.0, 0x00000000, 0x00000000
 
27
Other values (2393)
2519 
ValueCountFrequency (%) 
ERROR: openkey_set_protection Unable to autoload cardset in silent mode1780.4%
 
caller=svchost.exe480.1%
 
6.3.9600.19101460.1%
 
C:\Windows\system32\sppwinob.dll, msft:spp/windowsfunctionality/agent/7.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/inherited/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/phone/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:rm/algorithm/pkey/detect, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/ActionScheduler/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/TaskScheduler/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/statecollector/pkey, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/volume/services/kms/1.0, 0x00000000, 0x00000000 C:\Windows\system32\sppobjs.dll, msft:spp/volume/services/kms/activationinfo/1.0, 0x00000000, 0x00000000 360.1%
 
C:\windows\system32\sppwinob.dll, msft:spp/windowsfunctionality/agent/7.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/inherited/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/phone/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:rm/algorithm/pkey/detect, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/ActionScheduler/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/TaskScheduler/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/statecollector/pkey, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/volume/services/kms/1.0, 0x00000000, 0x00000000 C:\windows\system32\sppobjs.dll, msft:spp/volume/services/kms/activationinfo/1.0, 0x00000000, 0x00000000 270.1%
 
[CLIENT: <local machine>],DS\svc.omsql.ds24< 0.1%
 
[CLIENT: <local machine>],NASW\SVC.CTNOSC.WSMT.SCOM18< 0.1%
 
EventID=1120 Update in Progress10< 0.1%
 
EventID=1118 Update Finished8< 0.1%
 
[CLIENT: 207.133.219.135],DS\svc.omaction.ds7< 0.1%
 
Other values (2388)24524.9%
 
(Missing)4714694.3%
 
2020-09-26T20:33:39.393847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2344 ?
Unique (%)82.1%
2020-09-26T20:33:39.584913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1922
Median length3
Mean length14.49846
Min length2
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
ldap: 0x20: 0000208D: NameErr: DSID-03100238, problem 2001 (NO_OBJECT), data 0, best match of: 'OU=Computers,OU=USAMMA,OU=AMLC,OU=AMC,OU=Detrick,OU=Installations,DC=nae,DC=ds,DC=army,DC=mil'
ValueCountFrequency (%) 
ldap: 0x20: 0000208D: NameErr: DSID-03100238, problem 2001 (NO_OBJECT), data 0, best match of: 'OU=Computers,OU=USAMMA,OU=AMLC,OU=AMC,OU=Detrick,OU=Installations,DC=nae,DC=ds,DC=army,DC=mil' 1< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:39.914032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:40.003826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:40.115495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length192
Median length3
Mean length3.00378
Min length3
Distinct2
Distinct (%)33.3%
Missing49994
Missing (%)> 99.9%
Memory size390.6 KiB
Denied by Policy Module
Denied by Policy Module 0x8007208d, The requester's Active Directory object could not be retrieved. CN=KNOXW6J8AATBT26,OU=_Baseline_Imaging,OU=Knox,OU=Installations,DC=nase,DC=ds,DC=army,DC=mil ldap: 0x20: 0000208D: NameErr: DSID-03100238, problem 2001 (NO_OBJECT), data 0, best match of: 'OU=_Baseline_Imaging,OU=Knox,OU=Installations,DC=nase,DC=ds,DC=army,DC=mil'
ValueCountFrequency (%) 
Denied by Policy Module4< 0.1%
 
Denied by Policy Module 0x8007208d, The requester's Active Directory object could not be retrieved. CN=KNOXW6J8AATBT26,OU=_Baseline_Imaging,OU=Knox,OU=Installations,DC=nase,DC=ds,DC=army,DC=mil ldap: 0x20: 0000208D: NameErr: DSID-03100238, problem 2001 (NO_OBJECT), data 0, best match of: 'OU=_Baseline_Imaging,OU=Knox,OU=Installations,DC=nase,DC=ds,DC=army,DC=mil' 2< 0.1%
 
(Missing)49994> 99.9%
 
2020-09-26T20:33:40.260138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:40.356878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:40.497504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length371
Median length3
Mean length3.01632
Min length3

EVENTDATA_DATA_DN
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
CN=DETRW05JAANB074,OU=Computers,OU=USAMMA,OU=AMLC,OU=AMC,OU=Detrick,OU=Installations,DC=nae,DC=ds,DC=army,DC=mil
ValueCountFrequency (%) 
CN=DETRW05JAANB074,OU=Computers,OU=USAMMA,OU=AMLC,OU=AMC,OU=Detrick,OU=Installations,DC=nae,DC=ds,DC=army,DC=mil1< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:40.616193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:40.685998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:40.769776image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length112
Median length3
Mean length3.00218
Min length3

EVENTDATA_DATA_DOMAINNAME
Categorical

MISSING

Distinct20
Distinct (%)0.1%
Missing11367
Missing (%)22.7%
Memory size390.6 KiB
NAE
8892 
NASW
6795 
NASE
5516 
NANW
4885 
nasw.ds.army.mil
3554 
Other values (15)
8991 
ValueCountFrequency (%) 
NAE889217.8%
 
NASW679513.6%
 
NASE551611.0%
 
NANW48859.8%
 
nasw.ds.army.mil35547.1%
 
nae19834.0%
 
nase.ds.army.mil17483.5%
 
nasw13962.8%
 
nase13072.6%
 
nae.ds.army.mil13052.6%
 
Other values (10)12522.5%
 
(Missing)1136722.7%
 
2020-09-26T20:33:40.885432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:41.000162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length16
Median length4
Mean length5.2202
Min length2
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
Directory object not found. 0x8007208d (WIN32: 8333 ERROR_DS_OBJ_NOT_FOUND)
ValueCountFrequency (%) 
Directory object not found. 0x8007208d (WIN32: 8333 ERROR_DS_OBJ_NOT_FOUND)1< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:41.120836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:41.207572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:41.307304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length75
Median length3
Mean length3.00144
Min length3

EVENTDATA_DATA_HOSTNAME
Categorical

MISSING

Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
BRAGA1NEVXD0001.nae.ds.army.mil
ValueCountFrequency (%) 
BRAGA1NEVXD0001.nae.ds.army.mil1< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:41.444937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:41.525720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:41.608498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length31
Median length3
Mean length3.00056
Min length3

EVENTDATA_DATA_PARAM1
Categorical

HIGH CARDINALITY
MISSING

Distinct63
Distinct (%)24.8%
Missing49746
Missing (%)99.5%
Memory size390.6 KiB
nae.ds.army.mil
 
14
172.17.32.94
 
10
147.169.56.140
 
10
10.53.88.226
 
7
10.53.9.57
 
7
Other values (58)
206 
ValueCountFrequency (%) 
nae.ds.army.mil14< 0.1%
 
172.17.32.9410< 0.1%
 
147.169.56.14010< 0.1%
 
10.53.88.2267< 0.1%
 
10.53.9.577< 0.1%
 
10.53.32.747< 0.1%
 
0000208F: NameErr: DSID-03100225, problem 2006 (BAD_NAME), data 8349, best match of: 'DC=#brokerAddr#,DC=nae.ds.army.mil,cn=MicrosoftDNS,DC=DomainDnsZones,DC=nae,DC=ds,DC=army,DC=mil'7< 0.1%
 
160.150.115.787< 0.1%
 
10.53.32.907< 0.1%
 
147.169.57.596< 0.1%
 
Other values (53)1720.3%
 
(Missing)4974699.5%
 
2020-09-26T20:33:41.757427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique12 ?
Unique (%)4.7%
2020-09-26T20:33:41.910022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length184
Median length3
Mean length3.07346
Min length3

EVENTDATA_DATA_PARAM2
Categorical

MISSING

Distinct13
Distinct (%)46.4%
Missing49972
Missing (%)99.9%
Memory size390.6 KiB
0000208F: NameErr: DSID-03100225, problem 2006 (BAD_NAME), data 8349, best match of: 'DC=#brokerAddr#,DC=nae.ds.army.mil,cn=MicrosoftDNS,DC=DomainDnsZones,DC=nae,DC=ds,DC=army,DC=mil'
13 
SuppressDuplicateDuration
.
 
1
nae.ds.army.mil.dns
 
1
nasw.
 
1
Other values (8)
ValueCountFrequency (%) 
0000208F: NameErr: DSID-03100225, problem 2006 (BAD_NAME), data 8349, best match of: 'DC=#brokerAddr#,DC=nae.ds.army.mil,cn=MicrosoftDNS,DC=DomainDnsZones,DC=nae,DC=ds,DC=army,DC=mil'13< 0.1%
 
SuppressDuplicateDuration4< 0.1%
 
.1< 0.1%
 
nae.ds.army.mil.dns1< 0.1%
 
nasw.1< 0.1%
 
generichost-71-189.hood.army.mil.1< 0.1%
 
hoodw4nhaaa1sw4.nasw.ds.army.mil.1< 0.1%
 
army.mil.1< 0.1%
 
rcccw4nhaaa1s02.nasw.ds.army.mil.1< 0.1%
 
service.ds.army.mil.dns1< 0.1%
 
Other values (3)3< 0.1%
 
(Missing)4997299.9%
 
2020-09-26T20:33:42.041708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique11 ?
Unique (%)39.3%
2020-09-26T20:33:42.163342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length184
Median length3
Mean length3.05212
Min length1

EVENTDATA_DATA_PARAM3
Categorical

MISSING
UNIFORM

Distinct13
Distinct (%)86.7%
Missing49985
Missing (%)> 99.9%
Memory size390.6 KiB
Software\Microsoft\COM3\Eventlog
Software\Microsoft\EventSystem\EventLog
BRAGA1HQVXD0001.dahq.ds.army.mil
MEADW4NHAAA1A01.nae.ds.army.mil
APGRW4NHAAA1NE3.nae.ds.army.mil
Other values (8)
ValueCountFrequency (%) 
Software\Microsoft\COM3\Eventlog2< 0.1%
 
Software\Microsoft\EventSystem\EventLog2< 0.1%
 
BRAGA1HQVXD0001.dahq.ds.army.mil1< 0.1%
 
MEADW4NHAAA1A01.nae.ds.army.mil1< 0.1%
 
APGRW4NHAAA1NE3.nae.ds.army.mil1< 0.1%
 
ORLAA1SEPHUB001.nase.ds.army.mil1< 0.1%
 
HAWTA1SWP000001.nasw.ds.army.mil1< 0.1%
 
GORDA1SEP000005.nase.ds.army.mil1< 0.1%
 
CAMPA1SEP000003.nase.ds.army.mil1< 0.1%
 
DRUMA1NEP000003.nae.ds.army.mil1< 0.1%
 
Other values (3)3< 0.1%
 
(Missing)49985> 99.9%
 
2020-09-26T20:33:42.289039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique11 ?
Unique (%)73.3%
2020-09-26T20:33:42.408687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length39
Median length3
Mean length3.00892
Min length3

EVENTDATA_DATA_REASON
Categorical

MISSING

Distinct2
Distinct (%)33.3%
Missing49994
Missing (%)> 99.9%
Memory size390.6 KiB
The DNS name is unavailable and cannot be added to the Subject Alternate name. 0x8009480f (-2146875377 CERTSRV_E_SUBJECT_DNS_REQUIRED)
Directory object not found. 0x8007208d (WIN32: 8333 ERROR_DS_OBJ_NOT_FOUND)
ValueCountFrequency (%) 
The DNS name is unavailable and cannot be added to the Subject Alternate name. 0x8009480f (-2146875377 CERTSRV_E_SUBJECT_DNS_REQUIRED)4< 0.1%
 
Directory object not found. 0x8007208d (WIN32: 8333 ERROR_DS_OBJ_NOT_FOUND)2< 0.1%
 
(Missing)49994> 99.9%
 
2020-09-26T20:33:42.534350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:42.619123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:42.726796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length134
Median length3
Mean length3.01336
Min length3

EVENTDATA_DATA_REQUESTID
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)100.0%
Missing49993
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1023088
Minimum1002957
Maximum1048641
Zeros0
Zeros (%)0.0%
Memory size390.6 KiB
2020-09-26T20:33:42.822593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1002957
5-th percentile1003666.2
Q11005422
median1005778
Q31046698
95-th percentile1048149.9
Maximum1048641
Range45684
Interquartile range (IQR)41276

Descriptive statistics

Standard deviation22719.65396
Coefficient of variation (CV)0.02220694013
Kurtosis-2.77755928
Mean1023088
Median Absolute Deviation (MAD)2821
Skewness0.3710156087
Sum7161616
Variance516182676
MonotocityNot monotonic
2020-09-26T20:33:42.923326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
10470041< 0.1%
 
10463921< 0.1%
 
10057781< 0.1%
 
10055231< 0.1%
 
10053211< 0.1%
 
10029571< 0.1%
 
10486411< 0.1%
 
(Missing)49993> 99.9%
 
ValueCountFrequency (%) 
10029571< 0.1%
 
10053211< 0.1%
 
10055231< 0.1%
 
10057781< 0.1%
 
10463921< 0.1%
 
ValueCountFrequency (%) 
10486411< 0.1%
 
10470041< 0.1%
 
10463921< 0.1%
 
10057781< 0.1%
 
10055231< 0.1%
 

EVENTDATA_DATA_SCHANNELNAME
Categorical

HIGH CARDINALITY
MISSING

Distinct27717
Distinct (%)59.3%
Missing3243
Missing (%)6.5%
Memory size390.6 KiB
LEWIA0P6064
 
1423
RRADA0DFIMSAN4
 
1146
RADFC2A11V007TT
 
407
RUCKA0011ARTS01
 
396
SAMHA02199
 
316
Other values (27712)
43069 
ValueCountFrequency (%) 
LEWIA0P606414232.8%
 
RRADA0DFIMSAN411462.3%
 
RADFC2A11V007TT4070.8%
 
RUCKA0011ARTS013960.8%
 
SAMHA021993160.6%
 
CARLP0PROWFE0013070.6%
 
REDSTONEAPP62100.4%
 
SAMHA022002020.4%
 
BELVA40315DM0581980.4%
 
BELVA00315DM1371610.3%
 
Other values (27707)4199184.0%
 
(Missing)32436.5%
 
2020-09-26T20:33:43.114566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique22304 ?
Unique (%)47.7%
2020-09-26T20:33:43.257186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length15
Mean length13.80028
Min length3

EVENTDATA_DATA_SCHANNELTYPE
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing3243
Missing (%)6.5%
Memory size390.6 KiB
2
45925 
3
 
832
ValueCountFrequency (%) 
24592591.8%
 
38321.7%
 
(Missing)32436.5%
 
2020-09-26T20:33:43.371911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:43.438732image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:43.517490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

EVENTDATA_DATA_SUBJECTNAME
Categorical

MISSING

Distinct5
Distinct (%)83.3%
Missing49994
Missing (%)> 99.9%
Memory size390.6 KiB
NASE\KNOXW6J8AATBT26$
NAE\DRUMW0XQAANBE45$
NASE\STEWW6TCAAWK532$
NASW\BLISW1J000NBZ8T$
NASE\BUCHW6XDAANB016$
ValueCountFrequency (%) 
NASE\KNOXW6J8AATBT26$2< 0.1%
 
NAE\DRUMW0XQAANBE45$1< 0.1%
 
NASE\STEWW6TCAAWK532$1< 0.1%
 
NASW\BLISW1J000NBZ8T$1< 0.1%
 
NASE\BUCHW6XDAANB016$1< 0.1%
 
(Missing)49994> 99.9%
 
2020-09-26T20:33:43.627228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)66.7%
2020-09-26T20:33:43.706982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:43.839077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length3
Mean length3.00214
Min length3

EVENTDATA_DATA_USERNAME
Categorical

HIGH CARDINALITY
MISSING

Distinct5386
Distinct (%)11.5%
Missing3243
Missing (%)6.5%
Memory size390.6 KiB
SVC.NESSUS1.NC1BRAG
 
3227
SVC.HOOD.CYBRSECSCAN
 
2218
svc.scans.lewi
 
1790
svc.acas.samh
 
1563
SVC.CAIRS.LEWI
 
1423
Other values (5381)
36536 
ValueCountFrequency (%) 
SVC.NESSUS1.NC1BRAG32276.5%
 
SVC.HOOD.CYBRSECSCAN22184.4%
 
svc.scans.lewi17903.6%
 
svc.acas.samh15633.1%
 
SVC.CAIRS.LEWI14232.8%
 
svc.camp.acaswks213932.8%
 
Svc.acas.belv11712.3%
 
svc.ruck.acas11132.2%
 
svc.retinascan.blis10062.0%
 
svc.scan.wsmr8751.8%
 
Other values (5376)3097862.0%
 
(Missing)32436.5%
 
2020-09-26T20:33:43.988595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4155 ?
Unique (%)8.9%
2020-09-26T20:33:44.135399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length15
Mean length14.83232
Min length3

EVENTDATA_DATA_WORKSTATIONNAME
Categorical

HIGH CARDINALITY
MISSING

Distinct4002
Distinct (%)8.9%
Missing5253
Missing (%)10.5%
Memory size390.6 KiB
LEWIC2P6062
 
1423
acas-atec152
 
620
MINWINPC
 
573
TOBYFW11CRR5FW1
 
551
acas-rde070
 
378
Other values (3997)
41202 
ValueCountFrequency (%) 
LEWIC2P606214232.8%
 
acas-atec1526201.2%
 
MINWINPC5731.1%
 
TOBYFW11CRR5FW15511.1%
 
acas-rde0703780.8%
 
RADFC2A11V004TT3440.7%
 
acas-atec1503280.7%
 
BRAGNETCB6NS0073200.6%
 
BRAGNETCB6NS0043190.6%
 
BRAGNETCB6NS0023150.6%
 
Other values (3992)3957679.2%
 
(Missing)525310.5%
 
2020-09-26T20:33:44.292979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2720 ?
Unique (%)6.1%
2020-09-26T20:33:44.439620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length15
Mean length13.40302
Min length2

EVENTDATA_NAME
Categorical

MISSING

Distinct12
Distinct (%)4.6%
Missing49740
Missing (%)99.5%
Memory size390.6 KiB
DNS_EVENT_BAD_UPDATE_PACKET
203 
DNS_EVENT_DS_ZONE_ENUM_FAILED
 
13
DNS_EVENT_DS_INTERFACE_ERROR
 
12
DNS_EVENT_ZONE_LOAD_OK
 
11
DNS_EVENT_BAD_ZONE_TRANSFER_REQUEST
 
8
Other values (7)
 
13
ValueCountFrequency (%) 
DNS_EVENT_BAD_UPDATE_PACKET2030.4%
 
DNS_EVENT_DS_ZONE_ENUM_FAILED13< 0.1%
 
DNS_EVENT_DS_INTERFACE_ERROR12< 0.1%
 
DNS_EVENT_ZONE_LOAD_OK11< 0.1%
 
DNS_EVENT_BAD_ZONE_TRANSFER_REQUEST8< 0.1%
 
MSG_DN_CERT_DENIED_WITH_INFO6< 0.1%
 
DNS_EVENT_FILE_OPEN_ERROR2< 0.1%
 
MSG_W_CERT_PUBLICATION_HOST_NAME1< 0.1%
 
DNS_EVENT_ZONE_LOAD_COMPLETE1< 0.1%
 
DNS_EVENT_STARTUP_OK1< 0.1%
 
Other values (2)2< 0.1%
 
(Missing)4974099.5%
 
2020-09-26T20:33:44.571267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5 ?
Unique (%)1.9%
2020-09-26T20:33:44.697896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length3
Mean length3.1258
Min length3

FILENAME_INGEST
Categorical

HIGH CARDINALITY

Distinct14146
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
ds.army.mil_huaca2issca0001_application_2020_09_09_huaca2issca0001-application-2020-09-09-23-06-05-746.xml.zip
 
289
ds.army.mil_huaca2issca0001_application_2020_09_12_huaca2issca0001-application-2020-09-12-09-29-03-922.xml.zip
 
239
ds.army.mil_braga2dsviss001_application_2020_09_12_braga2dsviss001-application-2020-09-12-03-41-45-077.xml.zip
 
224
ds.army.mil_huaca2issca0001_application_2020_09_13_huaca2issca0001-application-2020-09-13-14-49-28-852.xml.zip
 
182
ds.army.mil_huaca2issca0002_application_2020_09_11_huaca2issca0002-application-2020-09-11-05-25-12-607.xml.zip
 
178
Other values (14141)
48888 
ValueCountFrequency (%) 
ds.army.mil_huaca2issca0001_application_2020_09_09_huaca2issca0001-application-2020-09-09-23-06-05-746.xml.zip2890.6%
 
ds.army.mil_huaca2issca0001_application_2020_09_12_huaca2issca0001-application-2020-09-12-09-29-03-922.xml.zip2390.5%
 
ds.army.mil_braga2dsviss001_application_2020_09_12_braga2dsviss001-application-2020-09-12-03-41-45-077.xml.zip2240.4%
 
ds.army.mil_huaca2issca0001_application_2020_09_13_huaca2issca0001-application-2020-09-13-14-49-28-852.xml.zip1820.4%
 
ds.army.mil_huaca2issca0002_application_2020_09_11_huaca2issca0002-application-2020-09-11-05-25-12-607.xml.zip1780.4%
 
ds.army.mil_rcccw4nhaaa0rfs_application_2020_09_13_rcccw4nhaaa0rfs-application-2020-09-13-07-01-45-179.xml.zip1600.3%
 
ds.army.mil_rcccw4nhaaa0rfs_application_2020_09_10_rcccw4nhaaa0rfs-application-2020-09-10-13-45-45-534.xml.zip1310.3%
 
ds.army.mil_huaca0dsv0sql01_application_2020_09_10_huaca0dsv0sql01-application-2020-09-10-03-00-51-624.xml.zip950.2%
 
ds.army.mil_braga2dsviss002_application_2020_09_09_braga2dsviss002-application-2020-09-09-21-55-11-197.xml.zip,ds.army.mil_braga2dsviss002_application_2020_09_10_braga2dsviss002-application-2020-09-10-21-02-59-108.xml.zip780.2%
 
ds.army.mil_braga2dsviss002_application_2020_09_11_braga2dsviss002-application-2020-09-11-21-55-11-140.xml.zip,ds.army.mil_braga2dsviss002_application_2020_09_13_braga2dsviss002-application-2020-09-13-09-19-10-734.xml.zip680.1%
 
Other values (14136)4835696.7%
 
2020-09-26T20:33:44.864198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2853 ?
Unique (%)5.7%
2020-09-26T20:33:45.011805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length347
Median length101
Mean length105.35518
Min length96

LOCATION
Categorical

HIGH CARDINALITY
MISSING

Distinct77
Distinct (%)0.2%
Missing16962
Missing (%)33.9%
Memory size390.6 KiB
RADF
 
1956
RUCK
 
1675
BELV
 
1582
WSMR
 
1351
APGR
 
1351
Other values (72)
25123 
ValueCountFrequency (%) 
RADF19563.9%
 
RUCK16753.4%
 
BELV15823.2%
 
WSMR13512.7%
 
APGR13512.7%
 
CAMP12992.6%
 
HOOD10822.2%
 
ROCK10542.1%
 
RRAD10252.1%
 
POLK9111.8%
 
Other values (67)1975239.5%
 
(Missing)1696233.9%
 
2020-09-26T20:33:45.164396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:45.306017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.66076
Min length3
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
nasw.ds.army.mil
13560 
nae.ds.army.mil
12726 
nase.ds.army.mil
12363 
nanw.ds.army.mil
8813 
ds.army.mil
2118 
Other values (3)
 
420
ValueCountFrequency (%) 
nasw.ds.army.mil1356027.1%
 
nae.ds.army.mil1272625.5%
 
nase.ds.army.mil1236324.7%
 
nanw.ds.army.mil881317.6%
 
ds.army.mil21184.2%
 
dahq.ds.army.mil3820.8%
 
service.ds.army.mil310.1%
 
conus.ds.army.mil7< 0.1%
 
2020-09-26T20:33:45.429718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:45.519478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:45.700960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length19
Median length16
Mean length15.53568
Min length11

SITE_COLLECTION
Categorical

HIGH CARDINALITY

Distinct282
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
radfa1nep000002
 
1817
jblmw4nhaah0nw1
 
1638
bragw4nhaah0se4
 
1299
rucka1sep000001
 
1160
wsmra1swp000002
 
956
Other values (277)
43130 
ValueCountFrequency (%) 
radfa1nep00000218173.6%
 
jblmw4nhaah0nw116383.3%
 
bragw4nhaah0se412992.6%
 
rucka1sep00000111602.3%
 
wsmra1swp0000029561.9%
 
jbsaw4nhaah0sw38101.6%
 
jbsaw4nhaah0sw27911.6%
 
rocka1nwp0000027861.6%
 
campa1sep0000047781.6%
 
huaca2issca00017651.5%
 
Other values (272)3920078.4%
 
2020-09-26T20:33:46.089921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9 ?
Unique (%)< 0.1%
2020-09-26T20:33:46.238524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length15
Mean length15
Min length15

SYSTEM_CHANNEL
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
Microsoft-Windows-NTLM/Operational
46757 
Application
 
2678
DNS Server
 
253
Directory Service
 
204
DFS Replication
 
108
ValueCountFrequency (%) 
Microsoft-Windows-NTLM/Operational4675793.5%
 
Application26785.4%
 
DNS Server2530.5%
 
Directory Service2040.4%
 
DFS Replication1080.2%
 
2020-09-26T20:33:46.369172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:46.464916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:46.605540image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length34
Median length34
Mean length32.53628
Min length10

SYSTEM_COMPUTER
Categorical

HIGH CARDINALITY

Distinct282
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
RADFA1NEP000002.nae.ds.army.mil
 
1817
JBLMW4NHAAH0NW1.nanw.ds.army.mil
 
1638
BRAGW4NHAAH0SE4.nase.ds.army.mil
 
1299
RUCKA1SEP000001.nase.ds.army.mil
 
1160
WSMRA1SWP000002.nasw.ds.army.mil
 
956
Other values (277)
43130 
ValueCountFrequency (%) 
RADFA1NEP000002.nae.ds.army.mil18173.6%
 
JBLMW4NHAAH0NW1.nanw.ds.army.mil16383.3%
 
BRAGW4NHAAH0SE4.nase.ds.army.mil12992.6%
 
RUCKA1SEP000001.nase.ds.army.mil11602.3%
 
WSMRA1SWP000002.nasw.ds.army.mil9561.9%
 
JBSAW4NHAAH0SW3.nasw.ds.army.mil8101.6%
 
JBSAW4NHAAH0SW2.nasw.ds.army.mil7911.6%
 
ROCKA1NWP000002.nanw.ds.army.mil7861.6%
 
campa1sep000004.nase.ds.army.mil7781.6%
 
HUACA2ISSCA0001.ds.army.mil7651.5%
 
Other values (272)3920078.4%
 
2020-09-26T20:33:46.747196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9 ?
Unique (%)< 0.1%
2020-09-26T20:33:46.893769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length32
Mean length31.53568
Min length27

SYSTEM_COMPUTER_REVERSE
Categorical

HIGH CARDINALITY

Distinct282
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
mil.army.ds.nae.RADFA1NEP000002
 
1817
mil.army.ds.nanw.JBLMW4NHAAH0NW1
 
1638
mil.army.ds.nase.BRAGW4NHAAH0SE4
 
1299
mil.army.ds.nase.RUCKA1SEP000001
 
1160
mil.army.ds.nasw.WSMRA1SWP000002
 
956
Other values (277)
43130 
ValueCountFrequency (%) 
mil.army.ds.nae.RADFA1NEP00000218173.6%
 
mil.army.ds.nanw.JBLMW4NHAAH0NW116383.3%
 
mil.army.ds.nase.BRAGW4NHAAH0SE412992.6%
 
mil.army.ds.nase.RUCKA1SEP00000111602.3%
 
mil.army.ds.nasw.WSMRA1SWP0000029561.9%
 
mil.army.ds.nasw.JBSAW4NHAAH0SW38101.6%
 
mil.army.ds.nasw.JBSAW4NHAAH0SW27911.6%
 
mil.army.ds.nanw.ROCKA1NWP0000027861.6%
 
mil.army.ds.nase.campa1sep0000047781.6%
 
mil.army.ds.HUACA2ISSCA00017651.5%
 
Other values (272)3920078.4%
 
2020-09-26T20:33:47.045363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9 ?
Unique (%)< 0.1%
2020-09-26T20:33:47.192542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length35
Median length32
Mean length31.53568
Min length27

SYSTEM_EVENTID
Real number (ℝ≥0)

HIGH CORRELATION

Distinct112
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7591.73466
Minimum0
Maximum26009
Zeros2
Zeros (%)< 0.1%
Memory size390.6 KiB
2020-09-26T20:33:47.318242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1066
Q18004
median8004
Q38004
95-th percentile8004
Maximum26009
Range26009
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1851.887257
Coefficient of variation (CV)0.2439346658
Kurtosis13.48118963
Mean7591.73466
Median Absolute Deviation (MAD)0
Skewness-2.891594898
Sum379586733
Variance3429486.413
MonotocityNot monotonic
2020-09-26T20:33:47.447526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
80044547490.9%
 
113292.7%
 
80068321.7%
 
80054510.9%
 
24360.9%
 
55092030.4%
 
31790.4%
 
12261460.3%
 
18453950.2%
 
1003840.2%
 
Other values (102)7711.5%
 
ValueCountFrequency (%) 
02< 0.1%
 
113292.7%
 
24360.9%
 
31790.4%
 
41< 0.1%
 
ValueCountFrequency (%) 
260091< 0.1%
 
18453950.2%
 
16384470.1%
 
123081< 0.1%
 
122911< 0.1%
 

SYSTEM_EVENTID_QUALIFIERS
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)0.2%
Missing47031
Missing (%)94.1%
Infinite0
Infinite (%)0.0%
Mean20456.54732
Minimum0
Maximum49152
Zeros207
Zeros (%)0.4%
Memory size390.6 KiB
2020-09-26T20:33:47.550293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116384
median16384
Q316384
95-th percentile49152
Maximum49152
Range49152
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11436.16958
Coefficient of variation (CV)0.5590469104
Kurtosis1.049847758
Mean20456.54732
Median Absolute Deviation (MAD)0
Skewness0.9981560111
Sum60735489
Variance130785974.6
MonotocityNot monotonic
2020-09-26T20:33:47.646994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
1638420194.0%
 
327684931.0%
 
491522310.5%
 
02070.4%
 
819218< 0.1%
 
11< 0.1%
 
(Missing)4703194.1%
 
ValueCountFrequency (%) 
02070.4%
 
11< 0.1%
 
819218< 0.1%
 
1638420194.0%
 
327684931.0%
 
ValueCountFrequency (%) 
491522310.5%
 
327684931.0%
 
1638420194.0%
 
819218< 0.1%
 
11< 0.1%
 

SYSTEM_EVENTRECORDID
Real number (ℝ≥0)

HIGH CORRELATION

Distinct49998
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean545777847.4
Minimum804
Maximum3726796661
Zeros0
Zeros (%)0.0%
Memory size390.6 KiB
2020-09-26T20:33:47.783628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum804
5-th percentile20438143.8
Q1183448650.8
median401328394.5
Q3670812193.5
95-th percentile1923303092
Maximum3726796661
Range3726795857
Interquartile range (IQR)487363542.8

Descriptive statistics

Standard deviation532864281.2
Coefficient of variation (CV)0.976339153
Kurtosis5.517912812
Mean545777847.4
Median Absolute Deviation (MAD)230710277.5
Skewness2.117106019
Sum2.728889237e+13
Variance2.839443422e+17
MonotocityNot monotonic
2020-09-26T20:33:47.912284image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
942232< 0.1%
 
330992< 0.1%
 
6354431971< 0.1%
 
346350771< 0.1%
 
9815831861< 0.1%
 
748967201< 0.1%
 
716424471< 0.1%
 
7313913101< 0.1%
 
5175206631< 0.1%
 
2995131641< 0.1%
 
Other values (49988)49988> 99.9%
 
ValueCountFrequency (%) 
8041< 0.1%
 
8471< 0.1%
 
18151< 0.1%
 
18191< 0.1%
 
20121< 0.1%
 
ValueCountFrequency (%) 
37267966611< 0.1%
 
37267898781< 0.1%
 
37267897891< 0.1%
 
37267785351< 0.1%
 
37267769871< 0.1%
 

SYSTEM_EXECUTION_PROCESSID
Real number (ℝ≥0)

MISSING
SKEWED

Distinct143
Distinct (%)0.3%
Missing2372
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean851.9048459
Minimum0
Maximum15996
Zeros395
Zeros (%)0.8%
Memory size390.6 KiB
2020-09-26T20:33:48.048944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile684
Q1852
median872
Q3892
95-th percentile932
Maximum15996
Range15996
Interquartile range (IQR)40

Descriptive statistics

Standard deviation308.3068241
Coefficient of variation (CV)0.3619028881
Kurtosis1100.906041
Mean851.9048459
Median Absolute Deviation (MAD)20
Skewness29.09915413
Sum40574524
Variance95053.0978
MonotocityNot monotonic
2020-09-26T20:33:48.172588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
876552911.1%
 
86439197.8%
 
87233706.7%
 
90830906.2%
 
86829395.9%
 
86021994.4%
 
88021874.4%
 
91218413.7%
 
88417803.6%
 
92016063.2%
 
Other values (133)1916838.3%
 
(Missing)23724.7%
 
ValueCountFrequency (%) 
03950.8%
 
1281< 0.1%
 
4089< 0.1%
 
4402< 0.1%
 
4801< 0.1%
 
ValueCountFrequency (%) 
159961< 0.1%
 
158641< 0.1%
 
155721< 0.1%
 
151361< 0.1%
 
149201< 0.1%
 

SYSTEM_EXECUTION_THREADID
Real number (ℝ≥0)

MISSING

Distinct5249
Distinct (%)11.0%
Missing2372
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean10566.69186
Minimum0
Maximum24536
Zeros395
Zeros (%)0.8%
Memory size390.6 KiB
2020-09-26T20:33:48.308228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1556
Q17272
median10804
Q314360
95-th percentile18372
Maximum24536
Range24536
Interquartile range (IQR)7088

Descriptive statistics

Standard deviation5075.050181
Coefficient of variation (CV)0.4802875155
Kurtosis-0.5526653828
Mean10566.69186
Median Absolute Deviation (MAD)3552
Skewness-0.1430156309
Sum503270400
Variance25756134.34
MonotocityNot monotonic
2020-09-26T20:33:48.441871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
03950.8%
 
21081600.3%
 
74401330.3%
 
7161190.2%
 
74641060.2%
 
24161050.2%
 
61961050.2%
 
24361020.2%
 
1036980.2%
 
2156900.2%
 
Other values (5239)4621592.4%
 
(Missing)23724.7%
 
ValueCountFrequency (%) 
03950.8%
 
322< 0.1%
 
3617< 0.1%
 
1242< 0.1%
 
1281< 0.1%
 
ValueCountFrequency (%) 
245361< 0.1%
 
244921< 0.1%
 
244641< 0.1%
 
244121< 0.1%
 
239121< 0.1%
 

SYSTEM_KEYWORDS
Categorical

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
0x8000000000000000
46778 
0x80000000000000
 
2672
0x8000000000000002
 
203
0x8080000000000000
 
202
0xa0000000000000
 
95
Other values (5)
 
50
ValueCountFrequency (%) 
0x80000000000000004677893.6%
 
0x8000000000000026725.3%
 
0x80000000000000022030.4%
 
0x80800000000000002020.4%
 
0xa0000000000000950.2%
 
0x8000000000000010250.1%
 
0x800000000002000013< 0.1%
 
0x80000000000800008< 0.1%
 
0x80000000000010003< 0.1%
 
0x80000000000100001< 0.1%
 
2020-09-26T20:33:48.568386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-09-26T20:33:48.642222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:48.836670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length18
Mean length17.88932
Min length16

SYSTEM_LEVEL
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
4
48983 
3
 
513
2
 
293
0
 
211
ValueCountFrequency (%) 
44898398.0%
 
35131.0%
 
22930.6%
 
02110.4%
 
2020-09-26T20:33:48.953357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:49.027159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:49.125896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

SYSTEM_OPCODE
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing2372
Missing (%)4.7%
Memory size390.6 KiB
0
47627 
1
 
1
(Missing)
 
2372
ValueCountFrequency (%) 
04762795.3%
 
11< 0.1%
 
(Missing)23724.7%
 
2020-09-26T20:33:49.191751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct11
Distinct (%)1.8%
Missing49403
Missing (%)98.8%
Memory size390.6 KiB
Software Protection Platform Service
368 
NTDS Replication
166 
NTDS General
 
17
Perflib
 
13
NTDS Database
 
10
Other values (6)
 
23
ValueCountFrequency (%) 
Software Protection Platform Service3680.7%
 
NTDS Replication1660.3%
 
NTDS General17< 0.1%
 
Perflib13< 0.1%
 
NTDS Database10< 0.1%
 
PerfNet9< 0.1%
 
NTDS KCC6< 0.1%
 
NTDS LDAP3< 0.1%
 
COM+2< 0.1%
 
EventSystem2< 0.1%
 
(Missing)4940398.8%
 
2020-09-26T20:33:49.280482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.2%
2020-09-26T20:33:49.394236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length3
Mean length3.29428
Min length3

SYSTEM_PROVIDER_GUID
Categorical

MISSING

Distinct15
Distinct (%)< 0.1%
Missing2372
Missing (%)4.7%
Memory size390.6 KiB
E5BA83F6-07D0-46B1-8BC7-7E669A1D31DC
46757 
E23B33B0-C8C9-472C-A5F9-F2BDFEA0F156
 
368
71A551F5-C893-4849-886B-B5EC8502641E
 
253
0e8478c5-3605-4e8c-8497-1e730c959516
 
202
13B197BD-7CEE-4B4E-8DD0-59314CE374CE
 
13
Other values (10)
 
35
ValueCountFrequency (%) 
E5BA83F6-07D0-46B1-8BC7-7E669A1D31DC4675793.5%
 
E23B33B0-C8C9-472C-A5F9-F2BDFEA0F1563680.7%
 
71A551F5-C893-4849-886B-B5EC8502641E2530.5%
 
0e8478c5-3605-4e8c-8497-1e730c9595162020.4%
 
13B197BD-7CEE-4B4E-8DD0-59314CE374CE13< 0.1%
 
CAB2B8A5-49B9-4EEC-B1B0-FAC21DA05A3B9< 0.1%
 
6A71D062-9AFE-4F35-AD08-52134F85DFB97< 0.1%
 
122EE297-BB47-41AE-B265-1CA8D1886D406< 0.1%
 
0888E5EF-9B98-4695-979D-E92CE42472243< 0.1%
 
899daace-4868-4295-afcd-9eb8fb4975612< 0.1%
 
Other values (5)8< 0.1%
 
(Missing)23724.7%
 
2020-09-26T20:33:49.513935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-09-26T20:33:49.624077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length36
Mean length34.43448
Min length3
Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
Microsoft-Windows-Security-Netlogon
46757 
nCipherLog
 
1744
Microsoft-Windows-Security-SPP
 
368
Microsoft-Windows-DNS-Server-Service
 
253
Microsoft-Windows-ActiveDirectory_DomainService
 
202
Other values (33)
 
676
ValueCountFrequency (%) 
Microsoft-Windows-Security-Netlogon4675793.5%
 
nCipherLog17443.5%
 
Microsoft-Windows-Security-SPP3680.7%
 
Microsoft-Windows-DNS-Server-Service2530.5%
 
Microsoft-Windows-ActiveDirectory_DomainService2020.4%
 
nCipher CSP1780.4%
 
DFSR1080.2%
 
MSSQLSERVER950.2%
 
Windows Error Reporting770.2%
 
ESENT690.1%
 
Other values (28)1490.3%
 
2020-09-26T20:33:49.746785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8 ?
Unique (%)< 0.1%
2020-09-26T20:33:49.871417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length47
Median length35
Mean length33.8421
Min length3

SYSTEM_SECURITY_USERID
Categorical

MISSING

Distinct37
Distinct (%)0.1%
Missing2629
Missing (%)5.3%
Memory size390.6 KiB
S-1-5-18
47066 
S-1-5-7
 
197
S-1-5-21-583907252-1532298954-1801674531-51609
 
24
S-1-5-21-4101780369-38368224-130243791-4238293
 
20
S-1-5-21-583907252-1532298954-1801674531-51605
 
20
Other values (32)
 
44
ValueCountFrequency (%) 
S-1-5-184706694.1%
 
S-1-5-71970.4%
 
S-1-5-21-583907252-1532298954-1801674531-5160924< 0.1%
 
S-1-5-21-4101780369-38368224-130243791-423829320< 0.1%
 
S-1-5-21-583907252-1532298954-1801674531-5160520< 0.1%
 
S-1-5-21-583907252-1532298954-1801674531-5161011< 0.1%
 
S-1-5-21-583907252-1532298954-1801674531-516073< 0.1%
 
S-1-5-21-3676333592-1006736145-1283606961-2701701< 0.1%
 
S-1-5-21-507921405-1645522239-682003330-721121< 0.1%
 
S-1-5-21-3822721094-983390456-1902330015-107274491< 0.1%
 
Other values (27)270.1%
 
(Missing)26295.3%
 
2020-09-26T20:33:49.995658image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique30 ?
Unique (%)0.1%
2020-09-26T20:33:50.111619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length49
Median length8
Mean length7.8159
Min length3

SYSTEM_TASK
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.96948
Minimum0
Maximum100
Zeros2834
Zeros (%)5.7%
Memory size390.6 KiB
2020-09-26T20:33:50.208396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile2
Maximum100
Range100
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.519594312
Coefficient of variation (CV)1.279319573
Kurtosis1418.887118
Mean1.96948
Median Absolute Deviation (MAD)0
Skewness36.62829847
Sum98474
Variance6.348355497
MonotocityNot monotonic
2020-09-26T20:33:50.306100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
24675993.5%
 
028345.7%
 
51620.3%
 
4950.2%
 
1660.1%
 
100310.1%
 
1011< 0.1%
 
229< 0.1%
 
79< 0.1%
 
98< 0.1%
 
Other values (5)16< 0.1%
 
ValueCountFrequency (%) 
028345.7%
 
1660.1%
 
24675993.5%
 
35< 0.1%
 
4950.2%
 
ValueCountFrequency (%) 
100310.1%
 
229< 0.1%
 
184< 0.1%
 
161< 0.1%
 
123< 0.1%
 

SYSTEM_TIMECREATED_SYSTEMTIME
Categorical

HIGH CARDINALITY
UNIFORM

Distinct49939
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size390.6 KiB
2020-09-11T05:04:09Z
 
3
2020-09-11T06:59:40Z
 
2
2020-09-13T07:05:18Z
 
2
2020-09-11T08:00:05Z
 
2
2020-09-11T07:49:15.722Z
 
2
Other values (49934)
49989 
ValueCountFrequency (%) 
2020-09-11T05:04:09Z3< 0.1%
 
2020-09-11T06:59:40Z2< 0.1%
 
2020-09-13T07:05:18Z2< 0.1%
 
2020-09-11T08:00:05Z2< 0.1%
 
2020-09-11T07:49:15.722Z2< 0.1%
 
2020-09-11T03:04:07Z2< 0.1%
 
2020-09-09T01:15:06Z2< 0.1%
 
2020-09-11T20:25:24Z2< 0.1%
 
2020-09-11T18:10:19Z2< 0.1%
 
2020-09-09T02:45:22Z2< 0.1%
 
Other values (49929)49979> 99.9%
 
2020-09-26T20:33:50.529504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique49879 ?
Unique (%)99.8%
2020-09-26T20:33:50.667166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length24
Mean length23.6708
Min length20

SYSTEM_VERSION
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing2372
Missing (%)4.7%
Memory size390.6 KiB
0
47627 
2
 
1
ValueCountFrequency (%) 
04762795.3%
 
21< 0.1%
 
(Missing)23724.7%
 
2020-09-26T20:33:50.778870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-09-26T20:33:50.846724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:50.923355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3
Distinct8
Distinct (%)42.1%
Missing49981
Missing (%)> 99.9%
Memory size390.6 KiB
7E000000
0200000000000000
FEDF0300FFDF0300D6050000
DE930300DF930300D6050000
2CD303002DD30300D6050000
Other values (3)
ValueCountFrequency (%) 
7E0000009< 0.1%
 
02000000000000004< 0.1%
 
FEDF0300FFDF0300D60500001< 0.1%
 
DE930300DF930300D60500001< 0.1%
 
2CD303002DD30300D60500001< 0.1%
 
A8D203004ED30300A9D203004FD303001< 0.1%
 
C6840300C7840300D60500001< 0.1%
 
2EAA03002FAA0300D60500001< 0.1%
 
(Missing)49981> 99.9%
 
2020-09-26T20:33:51.037087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)31.6%
2020-09-26T20:33:51.141808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:51.342271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length3
Mean length3.00462
Min length3

USERDATA_EVENTXML_BINARYDATASIZE
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)21.1%
Missing49981
Missing (%)> 99.9%
Memory size390.6 KiB
4
12
8
16
ValueCountFrequency (%) 
49< 0.1%
 
125< 0.1%
 
84< 0.1%
 
161< 0.1%
 
(Missing)49981> 99.9%
 
2020-09-26T20:33:51.485412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)5.3%
2020-09-26T20:33:51.580191image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:51.697415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.00012
Min length3

USERDATA_EVENTXML_PARAM1
Categorical

MISSING

Distinct4
Distinct (%)21.1%
Missing49981
Missing (%)> 99.9%
Memory size390.6 KiB
NPSrvHost
WmiApRpl
BITS
InterceptCountersManager
ValueCountFrequency (%) 
NPSrvHost6< 0.1%
 
WmiApRpl6< 0.1%
 
BITS4< 0.1%
 
InterceptCountersManager3< 0.1%
 
(Missing)49981> 99.9%
 
2020-09-26T20:33:51.826071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:51.919820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:52.036508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length24
Median length3
Mean length3.00266
Min length3

USERDATA_EVENTXML_PARAM2
Categorical

MISSING

Distinct2
Distinct (%)20.0%
Missing49990
Missing (%)> 99.9%
Memory size390.6 KiB
WmiApRpl
C:\Windows\System32\bitsperf.dll
ValueCountFrequency (%) 
WmiApRpl6< 0.1%
 
C:\Windows\System32\bitsperf.dll4< 0.1%
 
(Missing)49990> 99.9%
 
2020-09-26T20:33:52.152199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-09-26T20:33:52.234977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:52.323771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length3
Mean length3.00292
Min length3
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
Active Directory Domain Services,CNG Key Isolation,DFS Replication,DNS Server,EMET_Agent,Encrypting File System (EFS),Intersite Messaging,Kerberos Key Distribution Center,Microsoft EMET Service,Netlogon,ProV,Security Accounts Manager
ValueCountFrequency (%) 
Active Directory Domain Services,CNG Key Isolation,DFS Replication,DNS Server,EMET_Agent,Encrypting File System (EFS),Intersite Messaging,Kerberos Key Distribution Center,Microsoft EMET Service,Netlogon,ProV,Security Accounts Manager1< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:52.433446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:52.804453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:52.888607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length233
Median length3
Mean length3.0046
Min length3
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
12
ValueCountFrequency (%) 
121< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:52.981360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:53.041201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:53.103068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.00002
Min length3
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
10
ValueCountFrequency (%) 
101< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:53.200775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)100.0%
2020-09-26T20:33:53.264634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:53.330458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.00002
Min length3
Distinct1
Distinct (%)100.0%
Missing49999
Missing (%)> 99.9%
Memory size390.6 KiB
0
 
1
(Missing)
49999 
ValueCountFrequency (%) 
01< 0.1%
 
(Missing)49999> 99.9%
 
2020-09-26T20:33:53.398278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct1
Distinct (%)50.0%
Missing49998
Missing (%)> 99.9%
Memory size390.6 KiB
0
 
2
(Missing)
49998 
ValueCountFrequency (%) 
02< 0.1%
 
(Missing)49998> 99.9%
 
2020-09-26T20:33:53.431188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

USERDATA_RMSESSIONEVENT_UTCSTARTTIME
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing49998
Missing (%)> 99.9%
Memory size390.6 KiB
2020-09-11T21:24:06.836866900Z
2020-09-09T05:29:10.333552700Z
ValueCountFrequency (%) 
2020-09-11T21:24:06.836866900Z1< 0.1%
 
2020-09-09T05:29:10.333552700Z1< 0.1%
 
(Missing)49998> 99.9%
 
2020-09-26T20:33:53.501967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)100.0%
2020-09-26T20:33:53.575802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:53.661541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length3
Mean length3.00108
Min length3

Interactions

2020-09-26T20:33:15.376027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:15.499698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:15.617352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:15.736033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:15.843775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:15.944475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.042246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.157902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.278581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.400255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.528944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.644631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.753340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.857062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:16.988709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.127307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.246022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.361719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.556160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.664871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.768593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.870320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:17.968090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.067823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.164567image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.260310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.355062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.449803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.542552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.640294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.735037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.826794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:18.918551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.009303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.100063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.190787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.279580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.369343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.462093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.551851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.640617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.731954image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.821711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:19.914464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.004223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.092954image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.182745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.274534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.367322image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.458079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.551803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.642593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.732349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:20.823075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.008186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.104896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.217627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.330292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.447978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.562278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.670986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.772715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.871451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:21.968198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.061940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.154660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.249439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.341193image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.432916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.524702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.620415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.714165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.804952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.893717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:22.983474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.073204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.161996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.259703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.350460image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.439223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:23.530011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-09-26T20:33:53.773274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-09-26T20:33:54.100405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-09-26T20:33:54.428555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-09-26T20:33:54.803521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-09-26T20:33:24.071571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:30.325979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:33.395762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-09-26T20:33:35.097821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

IdTimestampData TypeVisibilityARCHITECTUREDOMAINDOMAINCONTROLLERDOMAINCONTROLLERNUMBEREVENTDATA_BINARYEVENTDATA_DATAEVENTDATA_DATA_ADDITIONALERRORMESSAGEEVENTDATA_DATA_ADDITIONALINFORMATIONEVENTDATA_DATA_DNEVENTDATA_DATA_DOMAINNAMEEVENTDATA_DATA_ERRORMESSAGETEXTEVENTDATA_DATA_HOSTNAMEEVENTDATA_DATA_PARAM1EVENTDATA_DATA_PARAM2EVENTDATA_DATA_PARAM3EVENTDATA_DATA_REASONEVENTDATA_DATA_REQUESTIDEVENTDATA_DATA_SCHANNELNAMEEVENTDATA_DATA_SCHANNELTYPEEVENTDATA_DATA_SUBJECTNAMEEVENTDATA_DATA_USERNAMEEVENTDATA_DATA_WORKSTATIONNAMEEVENTDATA_NAMEFILENAME_INGESTLOCATIONNETWORK_COLLECTIONSITE_COLLECTIONSYSTEM_CHANNELSYSTEM_COMPUTERSYSTEM_COMPUTER_REVERSESYSTEM_EVENTIDSYSTEM_EVENTID_QUALIFIERSSYSTEM_EVENTRECORDIDSYSTEM_EXECUTION_PROCESSIDSYSTEM_EXECUTION_THREADIDSYSTEM_KEYWORDSSYSTEM_LEVELSYSTEM_OPCODESYSTEM_PROVIDER_EVENTSOURCENAMESYSTEM_PROVIDER_GUIDSYSTEM_PROVIDER_NAMESYSTEM_SECURITY_USERIDSYSTEM_TASKSYSTEM_TIMECREATED_SYSTEMTIMESYSTEM_VERSIONUSERDATA_EVENTXML_BINARYDATAUSERDATA_EVENTXML_BINARYDATASIZEUSERDATA_EVENTXML_PARAM1USERDATA_EVENTXML_PARAM2USERDATA_RMRESTARTEVENT_APPLICATIONS_APPLICATIONUSERDATA_RMRESTARTEVENT_NAPPLICATIONSUSERDATA_RMRESTARTEVENT_REBOOTREASONSUSERDATA_RMRESTARTEVENT_RMSESSIONIDUSERDATA_RMSESSIONEVENT_RMSESSIONIDUSERDATA_RMSESSIONEVENT_UTCSTARTTIME
0007f61f414ceb5b8f267cd0c39bc7f221599964934000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-12 22:42:14 t2252: nFast server: Notice: RemoteTarget Rt1 broke (RemoteServerFailed, INET/172.20.10.5/9004 (InvalidModule))NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_braga2dsviss002_application_2020_09_13_braga2dsviss002-application-2020-09-13-09-19-10-734.xml.zipNaNds.army.milbraga2dsviss002ApplicationBRAGA2DSVISS002.ds.army.milmil.army.ds.BRAGA2DSVISS002116384.024276631NaNNaN0x800000000000004NaNNaNNaNnCipherLogNaN02020-09-13T02:42:14ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
100d0863e16446a9c6a11019af2541f691599998754000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-13 05:05:54 t2320: Hardserver [FP]: Remote server error: NST Nc238707 shutting down whilst expecting a SetupMiddle message: (UserCancelled)NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_huaca2issca0001_application_2020_09_13_huaca2issca0001-application-2020-09-13-14-49-28-852.xml.zipNaNds.army.milhuaca2issca0001ApplicationHUACA2ISSCA0001.ds.army.milmil.army.ds.HUACA2ISSCA0001232768.034757683NaNNaN0x800000000000003NaNNaNNaNnCipherLogNaN02020-09-13T12:05:54ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
200d81116ba58fc1fff71ffc1e50f10a91599970054000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-12 21:07:34 t2400: Hardserver [FP]: Notice: Connection to 207.133.219.149:9004 failed: A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respondNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_huaca2issca0001_application_2020_09_13_huaca2issca0001-application-2020-09-13-14-49-28-852.xml.zipNaNds.army.milhuaca2issca0001ApplicationHUACA2ISSCA0001.ds.army.milmil.army.ds.HUACA2ISSCA0001116384.034738538NaNNaN0x800000000000004NaNNaNNaNnCipherLogNaN02020-09-13T04:07:34ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
300e47ce60a7977239ea4d92be99fe1891599990816000evtx-application-cU&FOUOPNEA11.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNnae.ds.army.mil_tobya1nep000001_application_2020_09_13_tobya1nep000001-application-2020-09-13-09-55-12-102.xml.zip,nae.ds.army.mil_tobya1nep000001_application_2020_09_13_tobya1nep000001-application-2020-09-13-21-55-12-547.xml.zipTOBYnae.ds.army.miltobya1nep000001ApplicationTOBYA1NEP000001.nae.ds.army.milmil.army.ds.nae.TOBYA1NEP00000190316384.02244440.00.00x8000000000000000.0Software Protection Platform ServiceE23B33B0-C8C9-472C-A5F9-F2BDFEA0F156Microsoft-Windows-Security-SPPNaN02020-09-13T09:53:36Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
40170600419ccc8b42361641554dcb9d51600018819000evtx-application-cU&FOUOPNEA13.0NaN" 1: 20e938bb-df44-45ee-bde1-4e4fe7477f37, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 2: 2e7a9ad1-a849-4b56-babe-17d5a29fe4b4, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 3: 439e8c91-ff38-4ecb-ba0b-32658680c952, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 4: 5b338ef7-8d99-45cb-bb59-618bd328b4a4, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 5: 979d2e65-04b7-44c9-9d7b-ef4028168cba, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 6: 9db83b52-9904-4326-8957-ebe6feedf37c, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 7: 9e3fde40-d4b3-4c1d-9bde-32735aa19b39, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 8: acf1b4fd-1c55-4f2d-a60b-415ac958ad88, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 9: b3ca044e-a358-4d68-9883-aaa2941aca99, 1, 1 [(0 [0x00000000, 1, 0], [(?)( 1 0x00000000)(?)( 2 0x00000000 0 0 msft:rm/algorithm/volume/1.0 0x00000000 251412)(?)(?)( 10 0x00000000 msft:rm/algorithm/flags/1.0)(?)])(1 )(2 )] 10: c6b0fae3-70ea-4a98-95f2-587dc1ea4131, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 11: c7e5dd52-ef14-4bf6-bc71-1bf5f5794cd0, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 12: d3081572-e3f0-49f5-8b83-ec763c014570, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 13: d6992aac-29e7-452a-bf10-bbfb8ccabe59, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 14: dcb88f6f-b090-405b-850e-dabcccf3693f, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 15: f002931d-5536-4908-8d93-40ae584e24d6, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] 16: 9d0bb49b-21a1-4354-9981-ec5dd9393961, 1, 0 [(0 [0xC004F014, 0, 0], [(?)(?)(?)(?)(?)(?)(?)(?)])(1 )(2 )] ",55c92734-d682-4d71-983e-d6ec3f16059fNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNnae.ds.army.mil_druma1nep000003_application_2020_09_13_druma1nep000003-application-2020-09-13-21-55-11-293.xml.zipDRUMnae.ds.army.mildruma1nep000003ApplicationDRUMA1NEP000003.nae.ds.army.milmil.army.ds.nae.DRUMA1NEP000003100316384.01467900.00.00x8000000000000040.0Software Protection Platform ServiceE23B33B0-C8C9-472C-A5F9-F2BDFEA0F156Microsoft-Windows-Security-SPPNaN02020-09-13T17:40:19Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5028f97897fd8765d8afa22eeecc53e741600027481000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-13 16:04:41 t2252: nFast server: Notice: CreateClient (v1) pid: 5088, process name: C:\Windows\system32\svchost.exeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_braga2dsviss002_application_2020_09_13_braga2dsviss002-application-2020-09-13-21-55-11-584.xml.zipNaNds.army.milbraga2dsviss002ApplicationBRAGA2DSVISS002.ds.army.milmil.army.ds.BRAGA2DSVISS002116384.024297264NaNNaN0x800000000000004NaNNaNNaNnCipherLogNaN02020-09-13T20:04:41ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
602a05ed461912f5346cdbe327c70f0531599961853000evtx-application-cU&FOUONaNNaNNaNNaNNaNcaller=svchost.exeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNnae.ds.army.mil_scotw4nhaaa1a03_application_2020_09_13_scotw4nhaaa1a03-application-2020-09-13-10-55-06-857.xml.zipNaNnae.ds.army.milscotw4nhaaa1a03ApplicationSCOTW4NHAAA1A03.nae.ds.army.milmil.army.ds.nae.SCOTW4NHAAA1A0390016384.0578710.00.00x8000000000000040.0Software Protection Platform ServiceE23B33B0-C8C9-472C-A5F9-F2BDFEA0F156Microsoft-Windows-Security-SPPNaN02020-09-13T01:50:53Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7030780151dbc85f4b8b0f30a43a7fcf61600018340000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-13 13:32:20 t2252: nFast server: Remote server error: NST Nc21259 received InsecureClose whilst expecting a SetupMiddle message: (InvalidModule)NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_braga2dsviss002_application_2020_09_13_braga2dsviss002-application-2020-09-13-21-55-11-584.xml.zipNaNds.army.milbraga2dsviss002ApplicationBRAGA2DSVISS002.ds.army.milmil.army.ds.BRAGA2DSVISS002232768.024293900NaNNaN0x800000000000003NaNNaNNaNnCipherLogNaN02020-09-13T17:32:20ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8030bf4ec18c13e2dfe4e8fe6bcbb14321599956182000evtx-application-cU&FOUONaNNaNNaNNaNNaN2020-09-12 17:16:22 t2276: Hardserver [FP]: Notice: RemoteTarget Rt1 broke (RemoteServerFailed, INET/172.20.10.5/9004 (UnknownKeyHash (hash supplied)))NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_rcccw4nhaaa0rfs_application_2020_09_13_rcccw4nhaaa0rfs-application-2020-09-13-07-01-45-179.xml.zipNaNds.army.milrcccw4nhaaa0rfsApplicationRCCCW4NHAAA0RFS.ds.army.milmil.army.ds.RCCCW4NHAAA0RFS116384.015925634NaNNaN0x800000000000004NaNNaNNaNnCipherLogNaN02020-09-13T00:16:22ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
904504e25af9d8836ddf69b871b8e4c731599997303000evtx-application-cU&FOUONaNNaNNaNNaNNaNERROR: openkey_set_protection Unable to autoload cardset in silent modeNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNds.army.mil_huaca2issca0001_application_2020_09_13_huaca2issca0001-application-2020-09-13-14-49-28-852.xml.zipNaNds.army.milhuaca2issca0001ApplicationHUACA2ISSCA0001.ds.army.milmil.army.ds.HUACA2ISSCA0001349152.034756602NaNNaN0x800000000000002NaNNaNNaNnCipher CSPNaN02020-09-13T11:41:43ZNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

IdTimestampData TypeVisibilityARCHITECTUREDOMAINDOMAINCONTROLLERDOMAINCONTROLLERNUMBEREVENTDATA_BINARYEVENTDATA_DATAEVENTDATA_DATA_ADDITIONALERRORMESSAGEEVENTDATA_DATA_ADDITIONALINFORMATIONEVENTDATA_DATA_DNEVENTDATA_DATA_DOMAINNAMEEVENTDATA_DATA_ERRORMESSAGETEXTEVENTDATA_DATA_HOSTNAMEEVENTDATA_DATA_PARAM1EVENTDATA_DATA_PARAM2EVENTDATA_DATA_PARAM3EVENTDATA_DATA_REASONEVENTDATA_DATA_REQUESTIDEVENTDATA_DATA_SCHANNELNAMEEVENTDATA_DATA_SCHANNELTYPEEVENTDATA_DATA_SUBJECTNAMEEVENTDATA_DATA_USERNAMEEVENTDATA_DATA_WORKSTATIONNAMEEVENTDATA_NAMEFILENAME_INGESTLOCATIONNETWORK_COLLECTIONSITE_COLLECTIONSYSTEM_CHANNELSYSTEM_COMPUTERSYSTEM_COMPUTER_REVERSESYSTEM_EVENTIDSYSTEM_EVENTID_QUALIFIERSSYSTEM_EVENTRECORDIDSYSTEM_EXECUTION_PROCESSIDSYSTEM_EXECUTION_THREADIDSYSTEM_KEYWORDSSYSTEM_LEVELSYSTEM_OPCODESYSTEM_PROVIDER_EVENTSOURCENAMESYSTEM_PROVIDER_GUIDSYSTEM_PROVIDER_NAMESYSTEM_SECURITY_USERIDSYSTEM_TASKSYSTEM_TIMECREATED_SYSTEMTIMESYSTEM_VERSIONUSERDATA_EVENTXML_BINARYDATAUSERDATA_EVENTXML_BINARYDATASIZEUSERDATA_EVENTXML_PARAM1USERDATA_EVENTXML_PARAM2USERDATA_RMRESTARTEVENT_APPLICATIONS_APPLICATIONUSERDATA_RMRESTARTEVENT_NAPPLICATIONSUSERDATA_RMRESTARTEVENT_REBOOTREASONSUSERDATA_RMRESTARTEVENT_RMSESSIONIDUSERDATA_RMSESSIONEVENT_RMSESSIONIDUSERDATA_RMSESSIONEVENT_UTCSTARTTIME
499900a37c3b0c2eeb07256763941cc451cdc1599989865867evtx-ntlm-cU&FOUOPSWA12.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNBLISW6CLAANBKJ12.0NaNsvc.retinascan.blisblisnetcb6ns001NaNnasw.ds.army.mil_blisa1swp000002_ntlm_2020_09_13_blisa1swp000002-ntlm-2020-09-13-09-42-52-265.xml.zipBLISnasw.ds.army.milblisa1swp000002Microsoft-Windows-NTLM/OperationalBLISA1SWP000002.nasw.ds.army.milmil.army.ds.nasw.BLISA1SWP0000028004NaN307045198912.08660.00x800000000000000040.0NaNE5BA83F6-07D0-46B1-8BC7-7E669A1D31DCMicrosoft-Windows-Security-NetlogonS-1-5-1822020-09-13T09:37:45.867Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
499910a37dbfb4c068736a3b9fc96db65236d1600008014744evtx-ntlm-cU&FOUOPSEA11.0NaNNaNNaNNaNNaNNASENaNNaNNaNNaNNaNNaNNaNBUCHW1H1AAWK6172.0NaNsvc.buch.ia.oaBUCHNETCB6NS001NaNnase.ds.army.mil_bucha1sep000001_ntlm_2020_09_13_bucha1sep000001-ntlm-2020-09-13-15-31-41-146.xml.zipBUCHnase.ds.army.milbucha1sep000001Microsoft-Windows-NTLM/OperationalBUCHA1SEP000001.nase.ds.army.milmil.army.ds.nase.BUCHA1SEP0000018004NaN19274149932.09020.00x800000000000000040.0NaNE5BA83F6-07D0-46B1-8BC7-7E669A1D31DCMicrosoft-Windows-Security-NetlogonS-1-5-1822020-09-13T14:40:14.744Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
499920a37f7542405dd2ed34de8aac74196631600012937459evtx-ntlm-cU&FOUOPSEA12.0NaNNaNNaNNaNNaNNASENaNNaNNaNNaNNaNNaNNaNBUCHW1H1AAWK3562.0NaNsvc.buch.ia.oaBUCHNETCB6NS001NaNnase.ds.army.mil_bucha1sep000002_ntlm_2020_09_13_bucha1sep000002-ntlm-2020-09-13-16-27-42-959.xml.zipBUCHnase.ds.army.milbucha1sep000002Microsoft-Windows-NTLM/OperationalBUCHA1SEP000002.nase.ds.army.milmil.army.ds.nase.BUCHA1SEP0000028004NaN16378109924.014360.00x800000000000000040.0NaNE5BA83F6-07D0-46B1-8BC7-7E669A1D31DCMicrosoft-Windows-Security-NetlogonS-1-5-1822020-09-13T16:02:17.459Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
499930a38076bd657b3002d3b0f781722adbc1600022667956evtx-ntlm-cU&FOUOPSWA11.0NaNNaNNaNNaNNaNNASWNaNNaNNaNNaNNaNNaNNaNWSMRW04WAAWKN602.0NaNsvc.scan.wsmracas-atec152NaNnasw.ds.army.mil_wsmra1swp000001_ntlm_2020_09_13_wsmra1swp000001-ntlm-2020-09-13-18-45-45-994.xml.zipWSMRnasw.ds.army.milwsmra1swp000001Microsoft-Windows-NTLM/OperationalWSMRA1SWP000001.nasw.ds.army.milmil.army.ds.nasw.WSMRA1SWP0000018004NaN1252494011880.0900.00x800000000000000040.0NaNE5BA83F6-07D0-46B1-8BC7-7E669A1D31DCMicrosoft-Windows-Security-NetlogonS-1-5-1822020-09-13T18:44:27.956Z0.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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